|
|
Absolute deviation, 绝对离差9 t/ }+ l, ^+ b I
Absolute number, 绝对数* B$ C' f. j: t1 q0 a4 ]' _
Absolute residuals, 绝对残差5 ?* B* w1 M' ~( H
Acceleration array, 加速度立体阵
+ j; _1 s; |- k& HAcceleration in an arbitrary direction, 任意方向上的加速度% i) [6 O2 _+ I6 `
Acceleration normal, 法向加速度
( o! L6 v0 b7 A6 r: f& m0 d" XAcceleration space dimension, 加速度空间的维数- F) F( N8 ]+ A* P) Q# j
Acceleration tangential, 切向加速度
4 E. a: L0 i/ d2 W1 O$ I1 {6 N+ CAcceleration vector, 加速度向量# E/ J @, \: [4 ~4 }3 R5 o; r
Acceptable hypothesis, 可接受假设2 ] J: ?) U2 d# g9 P6 N- l# w
Accumulation, 累积1 C, r0 j: z4 K, Y
Accuracy, 准确度" E$ F! q* y0 t1 q! R
Actual frequency, 实际频数
( ?, _* q% _% y: X( w% dAdaptive estimator, 自适应估计量- u+ g/ Y3 \ I7 J x# a
Addition, 相加
* Y9 Z% O: p% P' o* Y) h5 Y1 h& sAddition theorem, 加法定理
6 u: N3 u$ m2 lAdditivity, 可加性' P5 S* e q4 t$ {) D2 j
Adjusted rate, 调整率
- q7 a7 v F) o% O: C/ Z* j* zAdjusted value, 校正值
1 {1 E# ]3 D) @' n6 z7 mAdmissible error, 容许误差
/ G6 P0 h0 ]1 T! a! u VAggregation, 聚集性
( @* ?" m) {8 N" rAlternative hypothesis, 备择假设
, M2 |% w9 r" y- K4 cAmong groups, 组间3 R" l) J$ {' ^2 O1 P+ T
Amounts, 总量
9 ^8 d# ]6 |5 ? MAnalysis of correlation, 相关分析( a$ @& w0 V8 i5 Y6 o
Analysis of covariance, 协方差分析1 r. \0 k; s* y' g+ s0 Y2 c. p
Analysis of regression, 回归分析
' G1 O3 Q3 H& ?& J. Z% UAnalysis of time series, 时间序列分析
0 B) w6 W( P" {/ P7 [Analysis of variance, 方差分析
1 J8 a" s `( J( W9 AAngular transformation, 角转换' j6 W) N/ M; w' @, _! \7 ]5 W3 g: r
ANOVA （analysis of variance）, 方差分析
4 J, ]* m3 W" n( K7 w: S) QANOVA Models, 方差分析模型
4 f( h" m! u, Y& F8 P, w& CArcing, 弧/弧旋
7 U) q) h# y' X5 b( aArcsine transformation, 反正弦变换4 q0 d! h: a6 l$ o- s8 K8 Z n
Area under the curve, 曲线面积
5 u1 R$ y; P1 ~) [$ ]. \- W3 AAREG , 评估从一个时间点到下一个时间点回归相关时的误差 ' o l1 ]4 |7 ?' d) A2 u
ARIMA, 季节和非季节性单变量模型的极大似然估计 & q: o$ W7 y& \4 [
Arithmetic grid paper, 算术格纸
* t. K6 r9 V6 {5 f% l$ yArithmetic mean, 算术平均数; {/ k% K: c& u3 Q$ N: @: v0 |6 L
Arrhenius relation, 艾恩尼斯关系
: Y7 F2 ?( x! }7 f& l3 A0 ?Assessing fit, 拟合的评估0 Z* _) _0 Q0 u; R) N) w
Associative laws, 结合律
% m/ K, G) ?% P( @6 ^Asymmetric distribution, 非对称分布
; h Z* H9 N9 h2 |( |2 `Asymptotic bias, 渐近偏倚
2 i4 u/ `! {3 c( F' oAsymptotic efficiency, 渐近效率4 b5 T- w1 y$ L& n; d' O, a3 F$ `
Asymptotic variance, 渐近方差$ t% U" R( H- I! ~1 K x. |
Attributable risk, 归因危险度
' P' ~- b, G6 B* ]* @9 CAttribute data, 属性资料# n( ?& W; @/ l9 V
Attribution, 属性+ ?/ ?+ l+ D1 u: g: H0 n: J
Autocorrelation, 自相关
; y! [0 o3 A1 E# Z4 V9 g8 VAutocorrelation of residuals, 残差的自相关* A) p! t2 o. ]0 h l4 o
Average, 平均数
7 D* @* f( P. l) v' o& n+ B( {Average confidence interval length, 平均置信区间长度/ g- s1 e7 {- h6 k
Average growth rate, 平均增长率
3 a( J# {8 ?/ U) j% YBar chart, 条形图9 ~2 t! [( I5 q9 z3 n" ]
Bar graph, 条形图
# e4 p% n0 f) c* s$ d/ r) jBase period, 基期7 p+ K. P9 \6 i, i2 _2 m1 {2 L
Bayes' theorem , Bayes定理
, w2 f8 {- l# ?Bell-shaped curve, 钟形曲线
+ B X1 J4 T% B5 kBernoulli distribution, 伯努力分布* Z: \5 d" Y( r6 D& r
Best-trim estimator, 最好切尾估计量3 n. [2 b1 }* {+ \
Bias, 偏性
2 |- H0 A5 Z; A( A# JBinary logistic regression, 二元逻辑斯蒂回归+ R J Q" B: ?
Binomial distribution, 二项分布 u9 y+ {5 A8 d) E* x. r
Bisquare, 双平方
3 P9 q3 N$ A3 P3 |0 PBivariate Correlate, 二变量相关6 d1 U% i4 z6 U# s6 P+ E
Bivariate normal distribution, 双变量正态分布
9 |5 e8 v4 S# K; \: Z1 d" N& {5 A: [Bivariate normal population, 双变量正态总体, P x) |( A, e1 W6 l* I) f
Biweight interval, 双权区间
1 v, P( b) F4 u' [2 HBiweight M-estimator, 双权M估计量# _7 V7 I4 V% U' l% x0 l
Block, 区组/配伍组/ J+ a F( a0 i. h& z
BMDP(Biomedical computer programs), BMDP统计软件包% l' e3 D) w( g8 X( Q, L
Boxplots, 箱线图/箱尾图
+ f( i5 N/ N) I+ E7 `/ R# x0 ZBreakdown bound, 崩溃界/崩溃点4 a+ c7 B8 ~% R$ u& `
Canonical correlation, 典型相关
; R0 H9 v/ t2 a6 E- @1 w3 xCaption, 纵标目; R6 w6 Q" ~8 d' y# S6 U& O
Case-control study, 病例对照研究& t, l4 S, c5 y' j c
Categorical variable, 分类变量
8 \3 |0 f7 v8 G& g& fCatenary, 悬链线6 @8 o7 L6 q3 U$ t& y
Cauchy distribution, 柯西分布
+ e: \4 r7 V4 hCause-and-effect relationship, 因果关系
( w9 o% S7 ^8 ?8 D/ }Cell, 单元% r1 h- x+ f7 g/ f# E6 ?8 a
Censoring, 终检0 K6 c$ w. h1 u F8 _3 S0 u5 h" ~
Center of symmetry, 对称中心
- B4 Y/ ]* m [; w! ECentering and scaling, 中心化和定标9 r6 c' D( G2 e! T* N' D
Central tendency, 集中趋势* H) V+ ~' D! \4 l% u3 ^; s/ ^
Central value, 中心值
( \4 w$ _" L- OCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
$ ]6 w2 t( [0 K! {* F. S8 uChance, 机遇; B7 j. T' z0 C! r( G8 A8 a
Chance error, 随机误差
# l# h( R# Y7 d# ]; wChance variable, 随机变量: Q; T1 @: {2 N; E: ]
Characteristic equation, 特征方程# W O% H- d, h2 E' Z6 H6 q
Characteristic root, 特征根( \7 Y4 f0 c% B" i
Characteristic vector, 特征向量
% T3 f% P$ l! l, Y2 }- `' VChebshev criterion of fit, 拟合的切比雪夫准则; Y8 y/ m' S( @* B `& h8 t
Chernoff faces, 切尔诺夫脸谱图
! D. B- ~' n# wChi-square test, 卡方检验/χ2检验
$ J# ~; V9 y% [1 k7 z7 YCholeskey decomposition, 乔洛斯基分解
2 D/ J# r- m. u: y4 sCircle chart, 圆图 ( J! Y" L0 {9 o# h6 ^
Class interval, 组距/ \' `4 g. X+ c* L4 D) p% a' C
Class mid-value, 组中值
5 [; W6 J$ R T: ~" uClass upper limit, 组上限9 |* N) }% Q+ L3 Z* ~
Classified variable, 分类变量
, t+ ^$ R: t8 k# R( X; b3 x$ L& ECluster analysis, 聚类分析) ~" v3 v- T* N/ p5 s
Cluster sampling, 整群抽样/ l; k0 S& C, K; ?4 E
Code, 代码
. C- l) \0 B5 z/ dCoded data, 编码数据1 C8 [2 j. W2 v( R: B% p
Coding, 编码
6 g, u- O9 B% ?Coefficient of contingency, 列联系数) S2 Q1 x) R. b# g% |# g5 F- |
Coefficient of determination, 决定系数. I5 D& H# F$ D7 C* s9 C N0 n4 X
Coefficient of multiple correlation, 多重相关系数
4 c5 S( K9 m. L2 T/ kCoefficient of partial correlation, 偏相关系数
$ e+ a$ l+ t; {Coefficient of production-moment correlation, 积差相关系数3 K3 c" p7 u* ~, T w- a: k. V5 g
Coefficient of rank correlation, 等级相关系数+ a3 V* w6 q9 A# A& J8 S% G3 S
Coefficient of regression, 回归系数/ W. P1 F7 P g/ b. t
Coefficient of skewness, 偏度系数! A: H% p t H1 b N/ C/ W
Coefficient of variation, 变异系数
1 }3 P2 y1 U; p6 Q- JCohort study, 队列研究
, ?( |2 E2 b+ G; c- WColumn, 列$ n& d( c: ^, w7 i* W
Column effect, 列效应
+ ^: r5 h- e) j3 V6 IColumn factor, 列因素# F5 ]2 v) d- ^4 b0 L
Combination pool, 合并
' @1 p# i" F' p o' ^3 A8 \' FCombinative table, 组合表
& I7 {* U h9 k: C9 C, RCommon factor, 共性因子0 I6 }$ W; {' O- n, O
Common regression coefficient, 公共回归系数
4 v% {; P% f2 M+ `, R5 u" {1 ^# Z# cCommon value, 共同值
! |# n; o) a: N7 c( q6 |% s8 O! cCommon variance, 公共方差
! l5 x+ E1 \4 ?: R6 c7 R! m4 q; ^Common variation, 公共变异
" \. Q2 l+ s7 s$ jCommunality variance, 共性方差
8 h: Q! e! f; q: a) V/ C5 T, V! NComparability, 可比性$ D: K9 i2 w% H. q8 \
Comparison of bathes, 批比较
* m1 n [1 r) \' m6 SComparison value, 比较值
0 T! F9 {. j* LCompartment model, 分部模型4 u% Z) Z. l$ o' ~4 l3 T
Compassion, 伸缩: D4 R, U/ S& k
Complement of an event, 补事件% A. Z0 ?1 P/ n7 K+ J" s6 D5 c
Complete association, 完全正相关" [$ R4 p+ s' t
Complete dissociation, 完全不相关
' W3 ~1 @+ v# Y: U" z3 l# FComplete statistics, 完备统计量# \% {' V" G/ ^9 i0 H
Completely randomized design, 完全随机化设计; \8 N1 Q1 M* `1 w* }' r
Composite event, 联合事件 ~7 u4 P% D% V! B
Composite events, 复合事件
7 w( d- h! x& PConcavity, 凹性
" Z) |# i9 r9 _, dConditional expectation, 条件期望
- q3 F7 ^0 g# z; j8 v# \Conditional likelihood, 条件似然
3 S& L& E) v- f3 f1 BConditional probability, 条件概率( m$ t G, L9 [9 ]- {9 j) J3 d$ e
Conditionally linear, 依条件线性
- z6 E/ m/ @! H1 x$ t8 i( T9 @Confidence interval, 置信区间0 Y9 y9 O: J$ \( z7 a1 {3 e
Confidence limit, 置信限
+ E0 g: U/ N0 N5 E% z" g: iConfidence lower limit, 置信下限9 {& W% G) X# k7 P# b" W5 Z. e
Confidence upper limit, 置信上限2 p4 r' p0 Y7 I0 `0 ?/ _ X8 Y
Confirmatory Factor Analysis , 验证性因子分析
8 w! S D: x9 L& GConfirmatory research, 证实性实验研究& k4 K& V" y& R# ~
Confounding factor, 混杂因素
7 x+ {6 t2 _3 tConjoint, 联合分析
2 v7 f0 T$ W8 ^Consistency, 相合性9 g6 c7 C: M: a0 F0 G% A
Consistency check, 一致性检验, O/ ^! |8 ]$ H' a$ `
Consistent asymptotically normal estimate, 相合渐近正态估计
/ Q" E" _5 l. |- P; Y i5 K6 A/ GConsistent estimate, 相合估计* Y8 ^: ~! M5 I! u0 w
Constrained nonlinear regression, 受约束非线性回归4 Q+ h- t/ U( O+ ^" Q
Constraint, 约束; g% D" \0 R4 j' A
Contaminated distribution, 污染分布+ V' [2 F/ d5 R7 S3 \$ z2 t c
Contaminated Gausssian, 污染高斯分布6 R% e @9 b! X6 j) T
Contaminated normal distribution, 污染正态分布) `& Z, M5 K2 j/ g: c
Contamination, 污染3 C' {6 C! w' C! R6 E- l, ?" }- X
Contamination model, 污染模型
; K- p, ]! K% t3 i0 t5 o, Z$ J% HContingency table, 列联表/ e9 f T) _' j$ _/ m
Contour, 边界线
; Z. r' E# N* lContribution rate, 贡献率
9 v M# ^) F) O& m& n0 C- gControl, 对照3 x8 c& L3 `* {4 y8 O2 b
Controlled experiments, 对照实验
9 x( k* z6 H1 H0 q0 BConventional depth, 常规深度
' {. b; E: l' \Convolution, 卷积' z- P/ i* h( O
Corrected factor, 校正因子4 l- G4 g6 _2 Z, i7 l
Corrected mean, 校正均值
6 x, e8 D" U6 o) }Correction coefficient, 校正系数# F2 p& H" @% ~$ j8 V+ h
Correctness, 正确性
1 w: H4 }4 Y& R. k+ ^, d ICorrelation coefficient, 相关系数
. V: b6 _3 G/ u# S) t, ACorrelation index, 相关指数4 w9 {( N5 ^- B5 P. g5 P* q
Correspondence, 对应; t+ c, O% H6 O
Counting, 计数
$ w' z" u6 M$ f3 VCounts, 计数/频数
: w( R. h, c6 m3 T& T' kCovariance, 协方差
4 p0 q! Y" y! p g4 ?, pCovariant, 共变
" h9 P, X' H/ ZCox Regression, Cox回归
; H* J& n' R( G0 ?$ J) `& `Criteria for fitting, 拟合准则' s* _6 K6 Z* F; d; c# `
Criteria of least squares, 最小二乘准则! z# ]. g/ e9 |( o, ?5 d g P
Critical ratio, 临界比
( Y' I" x' @, |5 ?Critical region, 拒绝域1 k; I) S' d6 i6 [
Critical value, 临界值4 R! G d: z7 e6 }9 j
Cross-over design, 交叉设计$ E0 C1 k/ F/ H
Cross-section analysis, 横断面分析; {' M B$ X2 _7 W
Cross-section survey, 横断面调查
( B1 _' b- Y3 t( D$ _1 t+ vCrosstabs , 交叉表 6 y& ]& _) P2 J, m' W
Cross-tabulation table, 复合表
( m; \/ G, g$ tCube root, 立方根
$ O7 E9 v6 q+ J1 z5 s( UCumulative distribution function, 分布函数
- G0 x% y1 {& [- c, b; m+ Q* VCumulative probability, 累计概率) V' q% n- o, S$ p
Curvature, 曲率/弯曲
# r: Z* R( O2 U/ J2 m4 t- gCurvature, 曲率; o" c# F/ b! s" z
Curve fit , 曲线拟和 . A& _ Q" i, F3 E1 l
Curve fitting, 曲线拟合
" l+ ?: u& O+ P4 }Curvilinear regression, 曲线回归
6 e9 R# h6 K/ d' L2 Y R6 e1 J, BCurvilinear relation, 曲线关系) @/ M% J, ~2 [
Cut-and-try method, 尝试法
; V5 d' J( J) |" WCycle, 周期6 D1 m& {6 z( Q# a# f
Cyclist, 周期性
$ n6 G: N* N7 z! i8 }* k- bD test, D检验
2 L/ W9 j/ W; N5 {' @) W3 qData acquisition, 资料收集* l- S8 J7 P K1 h6 b/ c
Data bank, 数据库
4 D( P( l0 [. G0 B/ }& S4 ^# DData capacity, 数据容量6 Y) t8 _! K. Z1 D
Data deficiencies, 数据缺乏2 X# F" K3 Z/ j% b
Data handling, 数据处理0 d/ D0 }. ^% D+ b: u
Data manipulation, 数据处理
) @8 J6 P9 X9 e1 n1 w8 E# T7 u0 L( kData processing, 数据处理
# d" G j0 \2 y# _Data reduction, 数据缩减
+ o" a$ _) O$ d h) z# vData set, 数据集
, B; E7 g% }7 `7 h- PData sources, 数据来源
1 s" N X, H2 u" S: d: S; U K$ M1 XData transformation, 数据变换8 r. D2 i6 a( K& \% A! B' w1 O8 z
Data validity, 数据有效性" P9 Z$ o6 p) Z6 A! n4 }9 h
Data-in, 数据输入
7 ]; _( z/ L, K2 NData-out, 数据输出
2 a H. f- J, x% R4 T# S* vDead time, 停滞期
# d: l' G, P8 [- d3 A4 ]; ?Degree of freedom, 自由度5 P. ]# O" v1 n2 U
Degree of precision, 精密度
- z4 P% K1 @/ _- DDegree of reliability, 可靠性程度 Y) b# ~2 N0 H$ `8 K8 B
Degression, 递减
, u$ g$ p5 P4 u% S! `' R5 g5 _. y! HDensity function, 密度函数7 `& d# @0 y- X2 `' g l2 h
Density of data points, 数据点的密度. k! z9 o9 @3 T' W! ^& |% f
Dependent variable, 应变量/依变量/因变量
0 W: f/ C q) R- h+ f) zDependent variable, 因变量( i( R0 J% |4 i) V* F7 v! t! ?: P" B* c
Depth, 深度& ^0 [- V; H6 A" ]' |4 X7 d
Derivative matrix, 导数矩阵- V& ~0 O1 g! [1 j8 Z; {8 H
Derivative-free methods, 无导数方法
O) s4 u. r1 T5 S" }& v$ EDesign, 设计4 d: J" n) V1 J/ Q" E0 H8 N
Determinacy, 确定性
% X1 A e N8 Y3 B. \" gDeterminant, 行列式. c+ U5 R, u+ c! S4 W
Determinant, 决定因素
3 }2 r2 e3 |, A9 uDeviation, 离差
& E( V9 I& U# X+ H5 IDeviation from average, 离均差: z' D) s% S/ |$ K5 U
Diagnostic plot, 诊断图
. v8 ?' r% n, ?# TDichotomous variable, 二分变量
6 A6 i2 q. k M& D" S, E4 oDifferential equation, 微分方程* I+ X% e% q: p! A5 T9 S( E+ b6 h& m) J
Direct standardization, 直接标准化法3 _- g0 E+ c& x4 ~1 E& m- D" X
Discrete variable, 离散型变量' G! U6 x( Z* _7 l+ k$ r$ p
DISCRIMINANT, 判断
8 _+ @$ X/ w1 Q5 C0 `9 ]Discriminant analysis, 判别分析) S* @/ G4 U7 r+ O' z0 J# W
Discriminant coefficient, 判别系数/ e k7 V! \5 b c5 b A! B# _
Discriminant function, 判别值& ~# b, i% ]* l. _
Dispersion, 散布/分散度
" [; v9 u+ }1 v% S! rDisproportional, 不成比例的
/ \% z0 E/ a6 O j# c; M+ e) JDisproportionate sub-class numbers, 不成比例次级组含量/ D @' n- v0 n2 G3 o) Q
Distribution free, 分布无关性/免分布6 _% s$ b" X/ ]0 o- D
Distribution shape, 分布形状
8 J4 ?/ U1 F& X7 U+ U) M5 J4 XDistribution-free method, 任意分布法
: M+ s( A6 ~0 V3 rDistributive laws, 分配律
' O, M$ O1 A! G( M5 R3 yDisturbance, 随机扰动项
' n1 w6 } }4 ~" O) }Dose response curve, 剂量反应曲线
- s; j0 w; t- r& X1 wDouble blind method, 双盲法
0 v$ ?2 i# O. t3 M5 @% n0 FDouble blind trial, 双盲试验9 U; q! ?9 m# J6 D
Double exponential distribution, 双指数分布3 ~3 U) r( m% W) O8 l' \
Double logarithmic, 双对数
8 N* z/ Z8 F9 o8 } ^# F$ _Downward rank, 降秩* q8 K ~$ A: ?
Dual-space plot, 对偶空间图
$ P0 y: h9 K, g5 P6 \- ?% \1 lDUD, 无导数方法
) y) N' y% j2 p/ u1 M1 {- x& dDuncan's new multiple range method, 新复极差法/Duncan新法
2 G7 M2 p- t+ ~4 M! b4 d$ \. bEffect, 实验效应3 `. y$ \ r P# d" Q
Eigenvalue, 特征值$ M: j/ w( q' l E+ a3 e
Eigenvector, 特征向量
# v: p6 ^* F9 T) D% y2 Q$ L- KEllipse, 椭圆0 ^5 Y6 M( b5 k# s
Empirical distribution, 经验分布( ], k% v; v% L
Empirical probability, 经验概率单位: O9 R4 x) R; ?0 F3 K: u
Enumeration data, 计数资料
( F0 ]/ [# A3 uEqual sun-class number, 相等次级组含量' b$ L9 ]5 Q5 ]( d
Equally likely, 等可能1 ^# N' d! M9 _# g) W
Equivariance, 同变性5 u- t* s/ C% j: m3 N
Error, 误差/错误3 [2 v; n0 w9 y1 f0 v: K. A7 e
Error of estimate, 估计误差
% A# m- E; e7 [' x! x+ x+ R; tError type I, 第一类错误
& q5 {" D- I6 T- SError type II, 第二类错误, D+ p: c* f( z1 J ~ W# r2 F4 t' o" ]6 W
Estimand, 被估量
$ e6 ^4 n7 E6 S+ T fEstimated error mean squares, 估计误差均方# b. {/ B J$ f) M5 |
Estimated error sum of squares, 估计误差平方和0 M* o+ \: u0 z& N6 L; o% ~
Euclidean distance, 欧式距离, ?: F, |% ]; r/ c1 G! Y( i
Event, 事件: m# q; U& o, D- @
Event, 事件 v6 v$ J* c9 _; `" Z
Exceptional data point, 异常数据点. B! j7 z9 c3 u) c) E/ q: C
Expectation plane, 期望平面0 m% o% w( n- |, m [/ d
Expectation surface, 期望曲面
' u5 f+ V* ?8 r, T% kExpected values, 期望值4 Q. w( M. x- i d
Experiment, 实验% \, X5 E/ r* M* _
Experimental sampling, 试验抽样7 u( U9 ?7 i# A# H' \$ x2 u; m
Experimental unit, 试验单位7 l; F1 N: t9 z _
Explanatory variable, 说明变量1 `) l& D% P; m5 y4 ? g& s
Exploratory data analysis, 探索性数据分析
; p/ |- n$ Z) aExplore Summarize, 探索-摘要8 j ~ s; V$ l7 q: ^% s
Exponential curve, 指数曲线
+ J" c C9 i5 M4 k3 {Exponential growth, 指数式增长
3 @2 Q j2 p* F# T. K/ Y9 f% \8 BEXSMOOTH, 指数平滑方法
" L: d' w# U7 F! t" A* z/ S. QExtended fit, 扩充拟合 g8 ~' k3 `# k) s1 |8 S
Extra parameter, 附加参数
4 W$ e; E2 M) mExtrapolation, 外推法) c; Z/ \( c( \1 d- M
Extreme observation, 末端观测值" m0 i3 E! O+ |" Y
Extremes, 极端值/极值
& a8 ?8 c$ ]! t9 z. mF distribution, F分布8 V+ O- ^; G8 j A+ s! S/ N: u
F test, F检验
, ^6 H v: U! j% J, KFactor, 因素/因子
! p+ {( b! q) AFactor analysis, 因子分析
- Q0 j; b3 i6 [Factor Analysis, 因子分析( U. p/ L# J1 n$ H5 S2 r% e
Factor score, 因子得分 1 ~! O5 N$ J/ X- e% i
Factorial, 阶乘
, y2 g8 v; z' X; f( DFactorial design, 析因试验设计
1 A; H& S4 l& I, \4 y UFalse negative, 假阴性, ^+ l7 K8 [" g9 ]9 w
False negative error, 假阴性错误/ X0 e3 X2 R3 q
Family of distributions, 分布族( l4 a8 c5 D E+ ~. ?" j
Family of estimators, 估计量族" l6 u" v0 h* {/ L4 Y2 h
Fanning, 扇面& f* {! B7 V7 J4 J% ]
Fatality rate, 病死率8 Y: p: f5 ?2 X5 R9 \1 Z, S
Field investigation, 现场调查
5 w* T+ J& C+ |2 IField survey, 现场调查6 o+ \4 R. Q J O/ c, d
Finite population, 有限总体
! s+ l$ T4 _6 g( D1 }Finite-sample, 有限样本
* a- o) m' V6 ~8 n( SFirst derivative, 一阶导数( k7 h8 I5 o4 L) Q5 Y) P
First principal component, 第一主成分7 q2 q* d2 F4 {8 |7 o, A+ {( l
First quartile, 第一四分位数0 D, ~3 @1 @! X- `0 B
Fisher information, 费雪信息量" q% c5 v! u0 o; V, s3 S7 @6 S
Fitted value, 拟合值
p: g" M- M- X2 d& L5 WFitting a curve, 曲线拟合
9 y' i* w ?8 z f7 zFixed base, 定基
% H+ {. ?% h% {6 f$ R8 `Fluctuation, 随机起伏
& S! r1 X1 O3 L, _) NForecast, 预测
* _: N' |; x0 @Four fold table, 四格表$ e! K) M8 j# ]! b: L7 R
Fourth, 四分点* T; N6 ~3 B+ ?1 |5 Z
Fraction blow, 左侧比率
1 s& j2 K+ w7 D2 ^; Y* dFractional error, 相对误差* n3 l }2 `$ A; f1 O2 j# O
Frequency, 频率
9 O8 q) T2 N r3 D, A" s- P+ F, l% A- FFrequency polygon, 频数多边图
$ H1 g/ t' V0 @) i" _# |$ QFrontier point, 界限点 i9 i Y! k5 v# e4 g! D: p5 D
Function relationship, 泛函关系: X. B& |) s* a/ I
Gamma distribution, 伽玛分布
4 M7 `6 J( e4 Q' w" }Gauss increment, 高斯增量
) E+ |9 B5 n( L0 a! fGaussian distribution, 高斯分布/正态分布8 Q. p# b. {5 S. J* T' o5 o* e
Gauss-Newton increment, 高斯-牛顿增量0 x; f6 L& H% ?) Y* C# N* \
General census, 全面普查( u8 X6 I" w- b6 N$ t
GENLOG (Generalized liner models), 广义线性模型 2 ?3 W! w5 f1 l1 T. {
Geometric mean, 几何平均数
, o+ D$ w& S" W" K j7 i5 R/ F$ @9 EGini's mean difference, 基尼均差* v" D% Y- l- s4 T: s4 I
GLM (General liner models), 一般线性模型 ; {6 i, O, J* h, h3 A! f) K. h
Goodness of fit, 拟和优度/配合度
8 d/ B0 x( y. A: GGradient of determinant, 行列式的梯度% o# ~2 }- H) f
Graeco-Latin square, 希腊拉丁方) K) B [3 A: l1 [' d
Grand mean, 总均值, A9 C8 o8 @6 \. D+ K- }" R9 k
Gross errors, 重大错误
& U# s; g, U* uGross-error sensitivity, 大错敏感度5 s H8 n9 X6 m. R: T+ a
Group averages, 分组平均
( V! q1 V8 \. [6 eGrouped data, 分组资料4 ~: R! w+ J/ K, n6 w2 c$ M
Guessed mean, 假定平均数
* x6 V5 s; S; ?: ?Half-life, 半衰期
6 @* X$ t) o( w" U' x BHampel M-estimators, 汉佩尔M估计量$ l) J! A8 r" X$ b4 B! b
Happenstance, 偶然事件
: \' c2 _: c1 R c9 RHarmonic mean, 调和均数0 P& ]& T' V' b: a: u
Hazard function, 风险均数
! [5 T% Z( P+ I; p" hHazard rate, 风险率. t' p3 u9 h' a/ U1 U& |
Heading, 标目
" r0 K/ T" F7 h: v* D! hHeavy-tailed distribution, 重尾分布0 | m, x; v; c e
Hessian array, 海森立体阵
$ i" P b& b, D# _8 X0 w6 _0 ?Heterogeneity, 不同质
1 X; r( m9 Y' [+ {: H# @Heterogeneity of variance, 方差不齐 + f0 b2 |' X" `) s% x
Hierarchical classification, 组内分组( e! b" g) T+ w$ d1 ~+ N
Hierarchical clustering method, 系统聚类法
, n; @ @- ~4 n _High-leverage point, 高杠杆率点
4 L- z+ h/ M9 O6 k+ gHILOGLINEAR, 多维列联表的层次对数线性模型
/ E5 J4 l: v7 e6 d7 f$ B; hHinge, 折叶点1 u1 R1 d3 n! x. e" E: h
Histogram, 直方图
, E- r% U' `, k6 S6 m( n# QHistorical cohort study, 历史性队列研究 6 j& e; m7 ]! q% H9 X6 g
Holes, 空洞
9 y& k& B5 C, f$ c, v+ F$ xHOMALS, 多重响应分析
; A; T! t7 C9 U- O. g$ b8 AHomogeneity of variance, 方差齐性$ e( ~8 q( h4 p3 s n% t: M
Homogeneity test, 齐性检验
0 p' ^% P& D1 i- W* zHuber M-estimators, 休伯M估计量2 n8 p9 `- B5 w7 p+ u5 ?! S
Hyperbola, 双曲线
5 {/ t+ A4 v4 V3 DHypothesis testing, 假设检验6 [- N+ {" D2 x+ H! g- Q3 m
Hypothetical universe, 假设总体( \# L6 y p/ d3 o4 n# i% e8 |
Impossible event, 不可能事件
& Y8 G8 J! Y) O/ z8 l. r7 QIndependence, 独立性
' C/ i } q6 N" oIndependent variable, 自变量6 t6 X: J( P% A
Index, 指标/指数7 ~% E: j3 @& k+ W: D$ M) y
Indirect standardization, 间接标准化法& y/ W1 `6 W. p0 U6 `
Individual, 个体3 T/ @/ H* m: A, O+ y
Inference band, 推断带- e) c7 N" f2 p; _
Infinite population, 无限总体
/ _0 f( D8 Y& ?* ?6 I* |# h* W( s7 {Infinitely great, 无穷大: z( F# C! O" r2 _3 E
Infinitely small, 无穷小
$ L* b3 k4 N) {# ]1 _6 mInfluence curve, 影响曲线4 e ~1 x# W. P7 j- Y* n
Information capacity, 信息容量 H) Z. G' L# q. M. A8 Y
Initial condition, 初始条件
( p+ P6 s' k7 t1 FInitial estimate, 初始估计值. Y! s5 \- U0 X
Initial level, 最初水平7 ~% `; S- M: A5 o- J8 }
Interaction, 交互作用
6 F- a/ t+ m! g% iInteraction terms, 交互作用项
! X/ O3 b2 ^' ]6 {% jIntercept, 截距+ T, j7 \" r# U5 |+ R- i
Interpolation, 内插法
2 x1 J; i! n( B* r1 ZInterquartile range, 四分位距: }$ B9 ]# E& ~) P% p" d
Interval estimation, 区间估计
c3 j3 z# O8 V B5 u* U' BIntervals of equal probability, 等概率区间
?7 e, j3 K' c" z2 f) \# uIntrinsic curvature, 固有曲率7 s0 _8 u' L1 `6 h( G
Invariance, 不变性2 d: H1 h3 n8 W% H# [3 k
Inverse matrix, 逆矩阵% z& y: K" S2 T0 M/ O, V+ Q9 C
Inverse probability, 逆概率6 D9 |6 w5 M V5 z% z, P4 v
Inverse sine transformation, 反正弦变换# z4 h) H0 X# h; p6 q& T3 d- P
Iteration, 迭代
) E s. q8 @+ d I5 IJacobian determinant, 雅可比行列式; u1 }3 [+ [- T3 A8 i) M# r6 \
Joint distribution function, 分布函数
2 [. o1 R& _8 }' EJoint probability, 联合概率0 S+ c4 l) v( ~4 g6 h- ^, w
Joint probability distribution, 联合概率分布
( j$ e5 \* u# u) j5 C$ z- Q8 {K means method, 逐步聚类法+ K4 s$ L5 O8 x9 ^
Kaplan-Meier, 评估事件的时间长度 ( N! }1 F4 P4 I; D
Kaplan-Merier chart, Kaplan-Merier图+ O- o+ r! r( ?6 W! g- F
Kendall's rank correlation, Kendall等级相关5 @* N9 g; \' a# Y# Y
Kinetic, 动力学
/ Q$ B8 W9 K: `Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验+ N6 C0 d v: N* q, U) A
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验. [. n- O& [2 {( X5 T
Kurtosis, 峰度
+ C, s# m; {; K7 H7 V: D2 C4 ~Lack of fit, 失拟
+ Y' n* Y1 v6 _0 R+ k6 |Ladder of powers, 幂阶梯* B% q) y V2 L# X- B
Lag, 滞后( t/ P( G* t: p9 g" L
Large sample, 大样本
* W* _1 P! U- d4 NLarge sample test, 大样本检验' P3 f4 i! h t3 _7 L8 B! c: R" m
Latin square, 拉丁方
d$ E! b8 X9 ~# N4 r; VLatin square design, 拉丁方设计/ P! m) z5 v: b5 t$ T: M7 a; l, ~/ I* G
Leakage, 泄漏" E- J, Y4 @3 O7 v% D
Least favorable configuration, 最不利构形
9 D9 N" d+ Q) W3 t3 @; W8 _" G& Q9 @Least favorable distribution, 最不利分布
& m$ k/ l$ g0 G3 p$ Y2 {$ }Least significant difference, 最小显著差法
4 K2 u: `! T7 y* oLeast square method, 最小二乘法
$ I' E/ G2 j0 U1 ILeast-absolute-residuals estimates, 最小绝对残差估计
5 J7 k5 j+ F( N6 vLeast-absolute-residuals fit, 最小绝对残差拟合
% k. \( c4 A- ]0 [Least-absolute-residuals line, 最小绝对残差线
' k' i* O9 B6 k# }( e1 R/ eLegend, 图例! h5 D$ r9 Y; k% D
L-estimator, L估计量9 v( h; L3 ^/ R9 n( @
L-estimator of location, 位置L估计量 B: O8 p) r; D- b) D% H7 e
L-estimator of scale, 尺度L估计量
0 R0 Y' _% J% dLevel, 水平/ S; o, ?+ U0 j n0 z% U o/ D
Life expectance, 预期期望寿命
# C$ C- K+ ?& b6 i; Y- jLife table, 寿命表8 f$ P+ C! V: X1 i3 \
Life table method, 生命表法& W5 K- _; N7 e! S
Light-tailed distribution, 轻尾分布
7 P: g- N: O+ p, E; [- h9 S8 JLikelihood function, 似然函数
1 X9 X" E7 _5 Z. x2 u4 ?Likelihood ratio, 似然比2 U. V; w5 i# ~6 x. I4 `
line graph, 线图
: U7 r+ z. z) x( f" p1 X1 I9 {# _0 ZLinear correlation, 直线相关. e4 ^$ D, G+ k7 D" o( F, f+ @1 Q$ a
Linear equation, 线性方程
6 c( a: l" X. F4 GLinear programming, 线性规划
" ~/ h8 `/ q+ Q% n3 BLinear regression, 直线回归& y+ \% }1 D( s$ i
Linear Regression, 线性回归' K3 _$ J0 k0 G! u
Linear trend, 线性趋势
. O% ]' ?! b, P! uLoading, 载荷
, q; g2 K; y1 C1 x# _! I i* }: oLocation and scale equivariance, 位置尺度同变性
' j1 _0 K c6 ~# ZLocation equivariance, 位置同变性
7 t3 U- \# F( l1 f- r1 oLocation invariance, 位置不变性
$ i! \8 w2 I# K1 _) c2 xLocation scale family, 位置尺度族' r, e i; g& f: w
Log rank test, 时序检验 % ~% s1 w' l: { \
Logarithmic curve, 对数曲线
$ K# ^2 {6 ]+ @; Z9 N' _ `Logarithmic normal distribution, 对数正态分布& i1 Z8 S6 q" s' O
Logarithmic scale, 对数尺度, R+ j& k) A& N! f! }5 B
Logarithmic transformation, 对数变换
+ }3 A3 @" x- z: V# RLogic check, 逻辑检查
: s, b4 b9 ~2 f. j" Y$ L% ~, I% ?# Y. E! qLogistic distribution, 逻辑斯特分布
+ W( r7 O# x+ c% e5 L* NLogit transformation, Logit转换+ N' M* Y p U9 d( l# w
LOGLINEAR, 多维列联表通用模型 ; @" w; h% ^0 [* m# l# L
Lognormal distribution, 对数正态分布9 t. E2 K9 K8 A% c1 W; D8 ]
Lost function, 损失函数
. f4 L' X" y6 y5 e2 yLow correlation, 低度相关
- }1 J1 c! Y9 z2 n! u3 _Lower limit, 下限
8 c6 \% z; z g1 M4 V$ P( ^Lowest-attained variance, 最小可达方差
& ~1 Z0 o: {! C1 A- @5 c4 _LSD, 最小显著差法的简称
2 v4 B. h1 s P4 P3 ~: bLurking variable, 潜在变量' g- p5 _, {& [5 T
Main effect, 主效应7 B6 Z R' V6 {3 ~% ]# V& W
Major heading, 主辞标目- j5 ^& ~- {0 o) `
Marginal density function, 边缘密度函数3 }* v `0 q6 e4 K! _
Marginal probability, 边缘概率0 l- A7 F x& `3 l% K, k
Marginal probability distribution, 边缘概率分布
+ v. r" L3 F' ^3 BMatched data, 配对资料& Z; E" u+ Z' N8 q
Matched distribution, 匹配过分布5 P% N8 n+ [9 @
Matching of distribution, 分布的匹配
% i; [ b. J& K. ^ f. T4 RMatching of transformation, 变换的匹配
. a! E7 [7 f3 D. `" v; yMathematical expectation, 数学期望
4 w# ]$ f3 [4 O& V3 r0 `* gMathematical model, 数学模型
1 {8 X" i% t& v1 ]" zMaximum L-estimator, 极大极小L 估计量
# l. p2 `% O+ S' c+ u) ?Maximum likelihood method, 最大似然法
+ W5 ?- Q! u. ]- _) hMean, 均数
. g: s4 B% k- |) Q oMean squares between groups, 组间均方
1 x$ O: X2 | U3 p# tMean squares within group, 组内均方
$ v+ i& G8 T* Z1 E! ^, f9 LMeans (Compare means), 均值-均值比较7 D$ D W8 P4 T3 W
Median, 中位数
. w, P! T9 U4 E6 h# ~% S$ l) ?3 V6 w sMedian effective dose, 半数效量
* u6 r. n, o4 rMedian lethal dose, 半数致死量8 X. K6 H3 B1 Z) u
Median polish, 中位数平滑
4 m* M( K1 K1 e3 KMedian test, 中位数检验) ?% e8 {9 x9 b& M$ @
Minimal sufficient statistic, 最小充分统计量4 u8 [' p- ^. T: M7 E
Minimum distance estimation, 最小距离估计
# a7 f3 j0 B8 B& T# U* V# AMinimum effective dose, 最小有效量9 J" s% r( j1 Y7 C) t
Minimum lethal dose, 最小致死量# J) q' G; \4 v3 `8 s0 B
Minimum variance estimator, 最小方差估计量! z0 d w$ z2 |& D; E9 q
MINITAB, 统计软件包# b8 T2 D* W7 |" E0 ?) G# u4 @
Minor heading, 宾词标目
$ m7 s& {! D5 x0 J! N4 GMissing data, 缺失值# S+ k3 j5 m6 W/ D
Model specification, 模型的确定
" O1 k3 h5 v9 h6 v0 l% AModeling Statistics , 模型统计
1 E! q$ N# J2 }. B* L$ wModels for outliers, 离群值模型+ E$ X4 }. U% f( F0 L
Modifying the model, 模型的修正
+ A. a+ E0 B; b" f0 G1 uModulus of continuity, 连续性模( c5 O" e& h8 U9 Y: N, w6 N+ L
Morbidity, 发病率
$ j% z! b1 |% U5 yMost favorable configuration, 最有利构形! H3 J3 m, I: X, `. N
Multidimensional Scaling (ASCAL), 多维尺度/多维标度: }6 k: j' L1 N( t D1 t+ q( U: F& {7 B/ s
Multinomial Logistic Regression , 多项逻辑斯蒂回归
1 f9 S1 M" T: h8 ?) VMultiple comparison, 多重比较# `6 }0 Z3 D; K$ y3 {# ]
Multiple correlation , 复相关; @3 H' w$ n( x/ ^7 \
Multiple covariance, 多元协方差
3 t0 z; `* k! q, X2 ~Multiple linear regression, 多元线性回归6 j$ @' Q* r6 @6 E1 O9 b
Multiple response , 多重选项+ l4 i. n0 u6 k6 u/ Q; O
Multiple solutions, 多解
2 c" q% k2 z0 V' ^, e# L$ hMultiplication theorem, 乘法定理
, q; y2 p$ Y+ a: j- K, I+ tMultiresponse, 多元响应4 O1 F9 R% x" F$ j& K
Multi-stage sampling, 多阶段抽样2 {. y: o" C# {$ V4 m
Multivariate T distribution, 多元T分布
5 `/ A0 G' l7 P3 G dMutual exclusive, 互不相容4 @# k& x: Z6 X# D- i: Z4 r) y
Mutual independence, 互相独立
' T0 I3 u; h6 f8 d1 S; i( @Natural boundary, 自然边界
4 V% C. B0 c9 O$ L8 z+ L WNatural dead, 自然死亡
4 w1 q" d$ K. p% F9 {Natural zero, 自然零
$ V3 U, i# z5 YNegative correlation, 负相关/ @" l$ |1 m, u- W* d: r
Negative linear correlation, 负线性相关9 A" C1 a& a& x5 P. k
Negatively skewed, 负偏% ]) f/ ?' O( m7 {2 D9 [
Newman-Keuls method, q检验
7 }6 i+ V- O6 |: j, WNK method, q检验+ h5 j' L" {% O& r2 q
No statistical significance, 无统计意义8 i5 u' f% {9 Z- R8 _
Nominal variable, 名义变量
! T1 ]5 m/ O- J! L; t( xNonconstancy of variability, 变异的非定常性
2 R( p: k& ]/ r, w( JNonlinear regression, 非线性相关
/ U3 d& E3 X( b' w- ?4 C& u# t" k7 RNonparametric statistics, 非参数统计$ F6 k9 R% f4 [- ]1 A% A( @9 q S5 l
Nonparametric test, 非参数检验1 J# m- a, G5 p W F
Nonparametric tests, 非参数检验/ A w! u D6 S; a- g2 g
Normal deviate, 正态离差5 i( s$ j: H( |
Normal distribution, 正态分布
! k" I7 Z* K* l6 L) J" j9 }Normal equation, 正规方程组
/ q+ d7 L$ _% L% a7 O5 c; s( pNormal ranges, 正常范围) y/ a( e2 \0 ]' s+ S$ \6 @
Normal value, 正常值
8 b. a5 l2 }" }9 iNuisance parameter, 多余参数/讨厌参数+ G4 @9 G( Y) C3 S A8 ~
Null hypothesis, 无效假设 ) a a Y9 i# a* F- W
Numerical variable, 数值变量# O- y/ L) d& z" M; E/ \" a% C
Objective function, 目标函数
9 m! \4 z, t% M5 s1 p/ S8 J5 S( DObservation unit, 观察单位
8 t$ A7 ?5 b! O- HObserved value, 观察值
* F7 }4 W3 L% }$ u$ qOne sided test, 单侧检验, Q1 |* g: z6 C% Q
One-way analysis of variance, 单因素方差分析
3 E- s1 {: A0 L$ Q9 j4 @Oneway ANOVA , 单因素方差分析. H* z' F7 N# H& J- o5 A- G( H
Open sequential trial, 开放型序贯设计
- T! n! [2 z# p+ R5 y7 DOptrim, 优切尾
P' q( ]& q" ^; P7 ]3 D* v3 tOptrim efficiency, 优切尾效率) o. ^7 }4 ?# X( w( w5 W
Order statistics, 顺序统计量! H4 k1 Z5 R/ l$ H7 S s: G5 {
Ordered categories, 有序分类
6 r9 |$ e; S5 X. dOrdinal logistic regression , 序数逻辑斯蒂回归
2 w) F S/ N* P! ]- c, bOrdinal variable, 有序变量
- r/ ~# U6 n% x0 |0 `Orthogonal basis, 正交基
! g3 X- m& v2 l8 \& xOrthogonal design, 正交试验设计8 I& L6 N ]; r0 Y+ y
Orthogonality conditions, 正交条件
2 {& J" k: E* h& `ORTHOPLAN, 正交设计
; r; l: N. ~( [! Q: {5 ^Outlier cutoffs, 离群值截断点6 N/ U$ Y- l# r4 H3 L _
Outliers, 极端值* q% q9 d& _ ?4 N1 j6 i; O3 i
OVERALS , 多组变量的非线性正规相关
5 F9 V: m+ H1 e/ wOvershoot, 迭代过度1 `8 U" x5 f, x% |
Paired design, 配对设计
5 U0 w$ ^- w9 c) UPaired sample, 配对样本. s4 T* F0 d8 L* c
Pairwise slopes, 成对斜率- V) v$ [& z# ] Y
Parabola, 抛物线
& Y) F) ~0 y; E0 ?7 p7 lParallel tests, 平行试验0 c8 W" S: g L( T/ l; I; `
Parameter, 参数0 _- J' p: Q9 U* |# S
Parametric statistics, 参数统计
! E/ B% ]" F- ?Parametric test, 参数检验0 q: |6 f- Q- j# U8 e
Partial correlation, 偏相关+ F7 L( ]6 v3 t* u6 C8 a3 ]
Partial regression, 偏回归/ o$ K. h6 B0 s; |: F
Partial sorting, 偏排序
1 u) R( I L- I% G) l( Y$ {) r# M9 NPartials residuals, 偏残差
3 U6 D4 o4 h$ D8 OPattern, 模式
/ n0 P2 N' N+ J8 l$ NPearson curves, 皮尔逊曲线( a" a' W9 n6 J( K0 v7 W
Peeling, 退层
9 f/ K0 h9 x JPercent bar graph, 百分条形图7 a" p+ v& b' n" M) o' U" B
Percentage, 百分比
5 M: f+ ^8 P3 H! g4 F1 RPercentile, 百分位数
8 o! A: _. J* f! gPercentile curves, 百分位曲线2 n6 X1 X0 u u+ q" t
Periodicity, 周期性
& q9 \4 k! V0 ZPermutation, 排列
3 u2 v7 E6 J, `P-estimator, P估计量
! d0 a+ {8 r2 p: V2 X' PPie graph, 饼图& n4 L9 z* r3 B6 h* h3 a+ H ]$ n+ V
Pitman estimator, 皮特曼估计量
! G3 F4 `( Q2 H! d8 ^Pivot, 枢轴量& m% G' ~( M* f. B5 q8 |! o. j
Planar, 平坦4 b' I1 l) n& i1 r9 `% q: ^7 F
Planar assumption, 平面的假设
; T3 J' ]( N% {2 `$ n1 MPLANCARDS, 生成试验的计划卡8 h# I. ]8 ~: K) \8 _
Point estimation, 点估计- K/ ~6 h. P2 g( w% z+ R
Poisson distribution, 泊松分布
& Y/ }) _0 c" s w/ U- e- G5 r" OPolishing, 平滑
. u7 n$ [9 k# O0 _1 mPolled standard deviation, 合并标准差6 `. c$ T8 h' M2 g; g0 v
Polled variance, 合并方差# v; S' B. P9 n/ [# E
Polygon, 多边图5 `0 u" F* g% c# L3 D2 J
Polynomial, 多项式$ _: ?+ N0 O' }$ K/ R3 Y, S0 \: ^; Z
Polynomial curve, 多项式曲线
" B/ d# s% _0 ~ [/ nPopulation, 总体
8 b+ T0 t" M+ x9 n BPopulation attributable risk, 人群归因危险度
1 w/ G) x. V9 t2 i0 @( }+ j. T P) zPositive correlation, 正相关
, x% E5 j0 O: d0 y9 f" o% ?Positively skewed, 正偏' [! D a( q) o( z; o7 G9 S
Posterior distribution, 后验分布" ~# f2 b" ~# Z6 Q2 \/ O
Power of a test, 检验效能3 o' S0 B# a- T" W, t
Precision, 精密度) z5 x4 }! D. k2 X
Predicted value, 预测值
# J2 E5 `) t: j: fPreliminary analysis, 预备性分析
" _: B2 y$ m uPrincipal component analysis, 主成分分析
7 M2 U* U3 E; C Q+ F% [Prior distribution, 先验分布
- P4 O* I3 T2 S" d( S) W; L# cPrior probability, 先验概率
1 Z' T5 C2 F: ^5 e* EProbabilistic model, 概率模型
) k- X; Z) V( L: N) nprobability, 概率
/ Z3 {( ?# u" D: A) f* w! gProbability density, 概率密度
$ a# f2 z& Z% q+ x$ Y% X- z: d1 `/ sProduct moment, 乘积矩/协方差: Q$ s' h* ^! a; x! k5 C1 E; h* H
Profile trace, 截面迹图
" {. e; z7 j( c, X& o, R. ?/ }Proportion, 比/构成比
# d! r3 H" z, v! T& r& m, nProportion allocation in stratified random sampling, 按比例分层随机抽样- Y7 q, _5 m3 b# p* `6 m/ K' G8 F
Proportionate, 成比例; b) {" @$ G9 p$ C# f
Proportionate sub-class numbers, 成比例次级组含量+ \$ A7 Q$ |# }2 k: g, q4 e( w
Prospective study, 前瞻性调查
4 z7 t' ?# }! W$ n3 g L/ I7 JProximities, 亲近性
! E; A p: P! T8 w$ u6 mPseudo F test, 近似F检验 B, d) r. u0 |% E- k
Pseudo model, 近似模型
/ p# W6 y- u; |3 g1 i: @: x j! TPseudosigma, 伪标准差5 X4 R* Y& R U1 Z: Y# ~
Purposive sampling, 有目的抽样
9 ]* q% j8 b( Q$ Y& k- }QR decomposition, QR分解& \5 M7 S. J* O
Quadratic approximation, 二次近似9 H* s- ?% P4 ]0 G
Qualitative classification, 属性分类 ~* x0 `, a z
Qualitative method, 定性方法
1 Z2 T+ ]* e6 F* }) w! p+ ?& {Quantile-quantile plot, 分位数-分位数图/Q-Q图
0 ? R& }, A$ o# C |/ cQuantitative analysis, 定量分析
" B. K; v7 E3 `6 U8 g1 SQuartile, 四分位数
8 h+ I1 d* m! GQuick Cluster, 快速聚类& U! ?( U( s6 F+ n; A7 V
Radix sort, 基数排序
! c$ F' p9 x6 QRandom allocation, 随机化分组
& }. i4 d6 i! G0 JRandom blocks design, 随机区组设计
1 M- J$ P7 _) _+ {3 W' PRandom event, 随机事件
7 O/ p* U8 _6 G; e7 ^. ]& w1 GRandomization, 随机化" S3 I5 y3 y1 k, z& L3 ?: I
Range, 极差/全距
$ B x* _ h4 p5 y# L# pRank correlation, 等级相关5 M( L- ~1 q- s4 u
Rank sum test, 秩和检验
3 I) R" c }/ G; iRank test, 秩检验
* H, v( [' D8 y! b0 v) K0 z b7 J9 WRanked data, 等级资料4 w/ b$ t' O" G" y N8 F _0 F
Rate, 比率
: d4 n) q# A5 `# y) J; V% kRatio, 比例
0 V* V' c) D. R6 T; FRaw data, 原始资料
, r0 F0 _# v& U* V8 zRaw residual, 原始残差
! S* @$ S5 v: W" f3 P7 X1 U( ?, w; u2 ORayleigh's test, 雷氏检验
" ]& R3 o$ c: \6 G2 p2 mRayleigh's Z, 雷氏Z值 0 w4 w8 @% w, r3 Q; z- j
Reciprocal, 倒数/ F) X6 y2 r: B1 c0 V
Reciprocal transformation, 倒数变换% S' k# b" t1 W. I9 c! H- b8 b
Recording, 记录
|4 j5 S. j1 ]- n. w4 ]Redescending estimators, 回降估计量
3 p, ]! p3 Y3 P2 y9 G* c6 j* l; xReducing dimensions, 降维
: h- w1 \. P3 B# c: BRe-expression, 重新表达0 x$ d* s3 n, e) T9 n7 ~
Reference set, 标准组
4 d/ [+ N& V' @8 X7 m7 QRegion of acceptance, 接受域% P2 \. D) u6 f' L# _* f" G) {6 v. M
Regression coefficient, 回归系数& r+ }2 W, S- V: i- x7 g
Regression sum of square, 回归平方和! j* W2 |. J6 t/ z) C2 e& g
Rejection point, 拒绝点( i; o6 j" n( |. N
Relative dispersion, 相对离散度
/ ^" _" A! Y" s; K9 sRelative number, 相对数; A* F: ?& x& W/ D, s- O& o
Reliability, 可靠性
4 E& o# ]8 G) H4 b! g6 r) _Reparametrization, 重新设置参数
0 d0 U, H* G. W4 p* m7 w+ Y, |, mReplication, 重复) G& W1 L. U# O: K$ v2 b8 T
Report Summaries, 报告摘要' v; f3 r" H C+ r
Residual sum of square, 剩余平方和0 C1 J8 m& e4 S6 {+ ~, H' L3 N* d+ ^
Resistance, 耐抗性5 S l1 U0 c$ \4 g! R E
Resistant line, 耐抗线
0 l$ f% T& N6 y6 `Resistant technique, 耐抗技术
2 H& W# z4 W* y3 vR-estimator of location, 位置R估计量- }* V% B, Y- K, d- S
R-estimator of scale, 尺度R估计量
' A1 @4 k9 Z9 l/ RRetrospective study, 回顾性调查# [& J/ ^2 I0 p, h& J% _
Ridge trace, 岭迹( c" p) V4 b. i
Ridit analysis, Ridit分析
' d9 e9 I T! ]Rotation, 旋转
" E1 @1 b/ z6 p. n" h5 D' mRounding, 舍入- P+ R9 @ n* g) d
Row, 行. n; i! E9 g. V6 ~" h
Row effects, 行效应3 h/ ~2 u7 B" F
Row factor, 行因素
* |1 ?$ ^- F7 `RXC table, RXC表6 R) q* G0 _/ u: E7 n; S* x9 I
Sample, 样本
: ~, @* ]! o7 x0 r1 S; fSample regression coefficient, 样本回归系数4 Z/ Z/ Z. S7 l0 D
Sample size, 样本量
a* y! _4 r3 C& v ^$ H# jSample standard deviation, 样本标准差
2 @8 h3 \. n! M" i5 rSampling error, 抽样误差
& Q8 K* V3 I& `9 ~SAS(Statistical analysis system ), SAS统计软件包
+ K) c* \! K: L) F$ n- m; S- KScale, 尺度/量表, j4 N4 t& E" N/ t+ K9 |# g
Scatter diagram, 散点图& z; N9 R3 ^% g/ b- L
Schematic plot, 示意图/简图" \3 ]/ m/ M- l3 X* P2 Y9 E. l
Score test, 计分检验2 j0 |" ?/ [5 J+ U h4 M- J
Screening, 筛检4 o9 R, B7 n) `1 b6 S) Y9 `! s
SEASON, 季节分析 - n+ r# |0 K- ~& i# ^$ l
Second derivative, 二阶导数
& w' T& M$ [$ i9 X- TSecond principal component, 第二主成分6 [* c' c Y0 Y; @/ U
SEM (Structural equation modeling), 结构化方程模型 9 P. F' P: |& t/ }3 q
Semi-logarithmic graph, 半对数图: W) K2 @. c. I$ @4 g6 w8 G( Z
Semi-logarithmic paper, 半对数格纸) B- o/ p& A p# Y" d4 }# t* J J9 l
Sensitivity curve, 敏感度曲线5 p W0 N& L( C8 `8 ~# d; K
Sequential analysis, 贯序分析; ^6 z9 S0 Z/ H' Q7 t# c
Sequential data set, 顺序数据集 I3 C0 Z+ p( |4 T) y* Z8 m
Sequential design, 贯序设计+ D1 d* J( l$ ?, s. B1 r: ?
Sequential method, 贯序法
: U, G8 k' K7 {3 u' z! `- GSequential test, 贯序检验法
) @2 P( g7 e8 B# b& iSerial tests, 系列试验6 h2 E& R0 ~+ w6 `8 M
Short-cut method, 简捷法 2 }% ?# y# |0 n/ t3 s
Sigmoid curve, S形曲线2 b! Z# l: @0 k O2 j7 D3 b
Sign function, 正负号函数
' \- \8 \/ I. T- c% JSign test, 符号检验
N' E- I3 S& USigned rank, 符号秩% `" }) W$ L/ b7 T" R
Significance test, 显著性检验
2 K6 I9 F4 U0 N9 _6 k- |9 qSignificant figure, 有效数字0 A n, I* j5 G/ w# d
Simple cluster sampling, 简单整群抽样# ^6 o# y S0 b; p! ^
Simple correlation, 简单相关
% j1 b' X; O1 r3 ^4 E7 X% OSimple random sampling, 简单随机抽样. e( b+ D8 v/ O+ N
Simple regression, 简单回归* r- l* A! J: p/ `; \; z
simple table, 简单表2 [ l' ~& V/ o; W! X
Sine estimator, 正弦估计量# D3 g* B4 |1 H0 A
Single-valued estimate, 单值估计
% H+ Y" y9 S: C2 {+ iSingular matrix, 奇异矩阵
6 Z: a! G0 \* O% @- T0 ]2 XSkewed distribution, 偏斜分布
* {3 n' l4 F3 k+ Z1 U; ]9 SSkewness, 偏度
9 |5 v' g" @! E% A. S$ Y1 g- u3 ~# p3 DSlash distribution, 斜线分布4 b) |- S6 `% u& I: n
Slope, 斜率
$ l3 n( A% V& j% r, r, tSmirnov test, 斯米尔诺夫检验
' J1 f$ d1 C, kSource of variation, 变异来源8 H, S$ |9 I% e: O
Spearman rank correlation, 斯皮尔曼等级相关
' d# ~' Q" \) R. o2 {Specific factor, 特殊因子% O+ ?1 F7 K: L4 S& G4 L8 I
Specific factor variance, 特殊因子方差
( p% R/ D1 q/ |Spectra , 频谱 C0 B p: f7 O) \9 m
Spherical distribution, 球型正态分布( {7 E$ B1 S) e
Spread, 展布8 D7 P( X6 B- @% \2 \
SPSS(Statistical package for the social science), SPSS统计软件包
1 U3 W) E/ E7 K8 KSpurious correlation, 假性相关
4 m, ~# \; p6 }Square root transformation, 平方根变换* |; f4 |* k# Y6 g
Stabilizing variance, 稳定方差
0 P9 \. r8 K. M! ^Standard deviation, 标准差
6 Z. o6 r4 e I' { H, S- g! fStandard error, 标准误
# A4 |) i5 L; x' N9 l: M( x3 h3 jStandard error of difference, 差别的标准误
+ Z+ Z W" p: G" u% hStandard error of estimate, 标准估计误差) I2 q4 K( U D, g4 v
Standard error of rate, 率的标准误
. X1 D p& G" vStandard normal distribution, 标准正态分布
$ d" h+ T* W7 D+ B, I' [' }, `Standardization, 标准化
# H' g& y9 I2 Z* {Starting value, 起始值
( w ]8 G% |: f1 m* K2 iStatistic, 统计量
; W; ~8 B F. u2 M7 a" kStatistical control, 统计控制
3 K6 O4 o4 ]7 m. b4 {) UStatistical graph, 统计图3 x0 ^* W% U" F0 q2 D
Statistical inference, 统计推断4 Z: S9 x: f" r! j! _9 `, f
Statistical table, 统计表
+ [0 A$ L( Q/ YSteepest descent, 最速下降法
# F! D, ]& } s% I: Q$ \5 T. w8 R: XStem and leaf display, 茎叶图& w8 {9 C& o8 s; L
Step factor, 步长因子
' V" ?$ N8 R' a# B$ r/ GStepwise regression, 逐步回归$ `7 y" f4 s( }" e$ M
Storage, 存
# J$ ^6 q% w/ X( Q$ x E- tStrata, 层（复数）
. ]$ X( m0 z( I; NStratified sampling, 分层抽样
1 f' \& u0 P, {8 JStratified sampling, 分层抽样
* z: F; O0 S* j1 K7 _( k4 cStrength, 强度
( m$ }# ?5 t2 Y1 h6 g( o OStringency, 严密性
3 b% X! O, [0 Q) oStructural relationship, 结构关系" I1 n6 ?7 T8 m4 o* S- J
Studentized residual, 学生化残差/t化残差- z p* o# y: ] b M3 q0 o. n
Sub-class numbers, 次级组含量$ ^& c! `4 O! y" G& m
Subdividing, 分割
4 t) V Y; x+ F" V6 v {0 e. `Sufficient statistic, 充分统计量- m: s4 h$ \/ A+ a1 m1 z G
Sum of products, 积和5 U, n' S" ~' K+ ^( p& N( d
Sum of squares, 离差平方和" ?- ]& m1 u5 ~) S' ]* c
Sum of squares about regression, 回归平方和1 m5 H* w) E7 v: C$ @4 ]& u, H
Sum of squares between groups, 组间平方和& n& L4 L( @- i; |; `8 C2 f6 X
Sum of squares of partial regression, 偏回归平方和3 K* h8 Q/ Y- V0 z
Sure event, 必然事件5 u; \' S3 _% O
Survey, 调查
. D$ C8 k2 Y4 A uSurvival, 生存分析
/ S! Z# K5 X, U) D% Q7 ]. TSurvival rate, 生存率+ X0 I6 g% d) |0 ]# b
Suspended root gram, 悬吊根图
6 j0 H" E# ~# y1 D( M( wSymmetry, 对称( R6 l `% H9 u- G
Systematic error, 系统误差* m, R3 Q8 {0 k" v- p" d4 w. \" ^
Systematic sampling, 系统抽样& Q+ s$ I; w9 ]5 ^, N1 r
Tags, 标签
' d& i# E- [! Y7 VTail area, 尾部面积) ?9 E7 d$ Q' @5 d" G" Q& v
Tail length, 尾长, V8 k9 B, S/ j4 w
Tail weight, 尾重( p3 Z) C8 g" i6 \. Y6 \9 f. ^7 k& l
Tangent line, 切线
& q/ l; s9 s$ ~Target distribution, 目标分布
* _8 W9 x; C, p/ v6 d, Z8 KTaylor series, 泰勒级数( e5 V5 {. G3 T6 S
Tendency of dispersion, 离散趋势( z8 a# ~9 k* _6 ?4 b7 ~
Testing of hypotheses, 假设检验
* E$ k. R G9 j5 [1 O# d# I u: Y" STheoretical frequency, 理论频数5 d9 [ V1 t0 X+ ?9 \/ @
Time series, 时间序列* |/ }% T$ o; k, J
Tolerance interval, 容忍区间
; A( ]" n! R' ^0 aTolerance lower limit, 容忍下限$ F/ \/ ]2 i/ t' k) Q3 A
Tolerance upper limit, 容忍上限+ {+ j7 r0 t- i# T3 {' k, \8 m4 \ d
Torsion, 扰率
( c; g0 c9 T/ D( Z+ I4 aTotal sum of square, 总平方和1 K8 I" L$ x7 x, I* E4 V9 c! C4 M
Total variation, 总变异
0 N, R1 `+ p8 b' ^8 X3 { ^Transformation, 转换5 I t, k1 L- s6 L' V0 z7 `5 p
Treatment, 处理
) j' z8 h9 X$ S4 M. U2 T9 \" kTrend, 趋势
7 \! e* v1 \( r. m- V+ S% e7 Y- ITrend of percentage, 百分比趋势
L, V6 t( D0 _$ N2 ?! a2 `3 QTrial, 试验0 ^& v( g3 O D# w) `6 Z
Trial and error method, 试错法7 w& Z' j1 g/ D5 u7 x
Tuning constant, 细调常数, L) \1 D5 p$ h
Two sided test, 双向检验1 S" i- ~0 k' o/ H
Two-stage least squares, 二阶最小平方
/ z2 G6 V. R4 M, V) K0 zTwo-stage sampling, 二阶段抽样
6 \* \( ?! Q$ I! {/ pTwo-tailed test, 双侧检验, _2 n! ^1 c; l' O2 O
Two-way analysis of variance, 双因素方差分析$ p7 b$ y5 n. ^7 d
Two-way table, 双向表/ H3 t% A! g- x( B7 d
Type I error, 一类错误/α错误
! p+ u4 J. M: ]0 eType II error, 二类错误/β错误
6 a9 D" |1 Y' h3 h" M: t) _UMVU, 方差一致最小无偏估计简称
( I+ z1 x: x& O+ i4 hUnbiased estimate, 无偏估计
0 ~) V; j; B+ v% C( d" KUnconstrained nonlinear regression , 无约束非线性回归
6 E7 n k8 Q) v+ |$ {Unequal subclass number, 不等次级组含量- D+ |/ S+ S0 S4 k" Q4 }
Ungrouped data, 不分组资料
" Q( m9 u n. YUniform coordinate, 均匀坐标
$ Y& ~& J8 S( X; R/ lUniform distribution, 均匀分布
8 `: E/ a( k1 f, _" CUniformly minimum variance unbiased estimate, 方差一致最小无偏估计. t1 f. I1 n4 B
Unit, 单元: _* H) q5 r9 {+ a% o$ \
Unordered categories, 无序分类
+ P2 c( J$ o P( }4 I% QUpper limit, 上限: d0 O, [& S- b5 G3 S% N
Upward rank, 升秩
_6 B/ B# n* M* c P4 g! qVague concept, 模糊概念
. s" ]$ F, k* K% N+ z! yValidity, 有效性
3 {! \* ^- w6 S8 |VARCOMP (Variance component estimation), 方差元素估计
" U. ~, P. }" M' ?1 HVariability, 变异性
5 K' }8 h" F8 e4 b4 {Variable, 变量) f0 x% P* R1 V- E7 S U, m
Variance, 方差# t( ^6 A5 T# Y" O0 |8 t2 z; Q
Variation, 变异
0 `1 k6 o T7 r" g: UVarimax orthogonal rotation, 方差最大正交旋转
4 \8 I" s6 w& ], IVolume of distribution, 容积/ w P P/ g* k6 k6 s7 Q- T
W test, W检验
/ `0 @2 H4 f# vWeibull distribution, 威布尔分布7 n1 v& t1 n+ b" E9 K' h# T. n
Weight, 权数* P( G& ~% F' ~5 q0 @& w
Weighted Chi-square test, 加权卡方检验/Cochran检验$ K I1 r5 ~ U# ?
Weighted linear regression method, 加权直线回归1 g Y8 F) O2 D8 c
Weighted mean, 加权平均数
2 D( {" K I0 w6 c! M) U; W# @Weighted mean square, 加权平均方差- u6 e" j) }4 ?, I, |' h' O( q
Weighted sum of square, 加权平方和
# M8 j6 c3 d/ NWeighting coefficient, 权重系数
! v: _, o) M$ Y/ ]. N0 cWeighting method, 加权法
p' f* S$ p, R/ j# z& i: IW-estimation, W估计量4 y& w* y! Y. [. v4 K e
W-estimation of location, 位置W估计量
, W' K' ^6 y6 O! \! w" S, [Width, 宽度! t7 Y- C1 z. |9 ?
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
* h8 a3 C2 M+ TWild point, 野点/狂点
b7 o$ @+ T( u. tWild value, 野值/狂值+ a9 X9 J) x/ n7 U! a$ \
Winsorized mean, 缩尾均值
* i' g0 [) n/ Y, oWithdraw, 失访 ( G5 n2 p7 @* s& t( \9 h0 u1 @
Youden's index, 尤登指数4 f' H: G( m8 |- U' B; ], W, W2 c
Z test, Z检验% c+ f. F7 |4 Z1 _9 f& [$ ?
Zero correlation, 零相关, p! z3 ` F1 p% z. a, A+ d2 l
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
